textgen
Repository: textgen
Author: oobabooga · Source status: Clear source
Score 92Clear source
Manual reviewThe original local LLM interface.
Score basis：Clear source · Risk needs review · Universal
Author unclaimed
Universal
46.5K
Compare skills
Pick 2–4 skills and compare what really matters: fit, risk, install effort, and community signal.
Selected skills (2/4)
Comparison matrix
Highlights show current best; tooltip explains diff/best rules.
SAS-v2.1 diff rules / risk tag notes
Start with the matrix. Open this section when you need to understand audit grades, top threats, control gaps, and best-value highlights.
Suggested baseline
Search to add skills, or paste 2–4 comma-separated slugs.
How differences are detected
A row is marked different when selected skills have distinct values. Only-differences mode hides rows that are identical.
How best values are highlighted
Audit score, evidence confidence, trust score, and community signal prefer higher values; execution risk and install friction prefer lower values.
How to read risk tags
Risk tags come from SAS-v2.1 public-evidence signals and point to command, network, secret, context, or supply-chain items to review before install.
Selected audit signals
pi-mono
Execution risk：High
Threat tags：unexpected code execution, data exfiltration, human approval gap
Control gaps：missing license, broad permissions, shell without guardrails
firecrawl
Execution risk：High
Threat tags：unexpected code execution, data exfiltration, human approval gap
Control gaps：missing license, broad permissions, shell without guardrails
| Dimension | pi-mono | firecrawl |
|---|---|---|
| Source & provenance | ||
Provenance | badlogic/pi-mono | firecrawl/firecrawl |
| Community | ||
Stars | 35.3K | 108.8K |
Repository: awesome-design-md
Author: VoltAgent · Source status: Clear source
A collection of DESIGN.md files inspired by popular brand design systems.
Score basis：Clear source · Risk needs review · Universal
Repository: awesome-llm-apps
Author: Shubhamsaboo · Source status: Clear source
Collection of awesome LLM apps with AI Agents and RAG using OpenAI, Anthropic, Gemini and opensource models.
Score basis：Clear source · Risk needs review · Universal